mirror of
https://github.com/opencv/opencv.git
synced 2024-11-29 22:00:25 +08:00
96b2898f38
range in calcHist() changed from [0,255] to [0,256]. Otherwise, it won't count pixels with value 255. It can be verified taking sum of histogram values and checking it with image size.
113 lines
3.4 KiB
Python
Executable File
113 lines
3.4 KiB
Python
Executable File
#/usr/bin/env python
|
|
|
|
''' This is a sample for histogram plotting for RGB images and grayscale images for better understanding of colour distribution
|
|
|
|
Benefit : Learn how to draw histogram of images
|
|
Get familier with cv2.calcHist, cv2.equalizeHist,cv2.normalize and some drawing functions
|
|
|
|
Level : Beginner or Intermediate
|
|
|
|
Functions : 1) hist_curve : returns histogram of an image drawn as curves
|
|
2) hist_lines : return histogram of an image drawn as bins ( only for grayscale images )
|
|
|
|
Usage : python hist.py <image_file>
|
|
|
|
Abid Rahman 3/14/12 debug Gary Bradski
|
|
'''
|
|
|
|
import cv2
|
|
import numpy as np
|
|
|
|
bins = np.arange(256).reshape(256,1)
|
|
|
|
def hist_curve(im):
|
|
h = np.zeros((300,256,3))
|
|
if len(im.shape) == 2:
|
|
color = [(255,255,255)]
|
|
elif im.shape[2] == 3:
|
|
color = [ (255,0,0),(0,255,0),(0,0,255) ]
|
|
for ch, col in enumerate(color):
|
|
hist_item = cv2.calcHist([im],[ch],None,[256],[0,256])
|
|
cv2.normalize(hist_item,hist_item,0,255,cv2.NORM_MINMAX)
|
|
hist=np.int32(np.around(hist_item))
|
|
pts = np.int32(np.column_stack((bins,hist)))
|
|
cv2.polylines(h,[pts],False,col)
|
|
y=np.flipud(h)
|
|
return y
|
|
|
|
def hist_lines(im):
|
|
h = np.zeros((300,256,3))
|
|
if len(im.shape)!=2:
|
|
print "hist_lines applicable only for grayscale images"
|
|
#print "so converting image to grayscale for representation"
|
|
im = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
|
|
hist_item = cv2.calcHist([im],[0],None,[256],[0,256])
|
|
cv2.normalize(hist_item,hist_item,0,255,cv2.NORM_MINMAX)
|
|
hist=np.int32(np.around(hist_item))
|
|
for x,y in enumerate(hist):
|
|
cv2.line(h,(x,0),(x,y),(255,255,255))
|
|
y = np.flipud(h)
|
|
return y
|
|
|
|
|
|
if __name__ == '__main__':
|
|
|
|
import sys
|
|
|
|
if len(sys.argv)>1:
|
|
im = cv2.imread(sys.argv[1])
|
|
else :
|
|
im = cv2.imread('../cpp/lena.jpg')
|
|
print "usage : python hist.py <image_file>"
|
|
|
|
|
|
gray = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
|
|
|
|
|
|
print ''' Histogram plotting \n
|
|
Keymap :\n
|
|
a - show histogram for color image in curve mode \n
|
|
b - show histogram in bin mode \n
|
|
c - show equalized histogram (always in bin mode) \n
|
|
d - show histogram for color image in curve mode \n
|
|
e - show histogram for a normalized image in curve mode \n
|
|
Esc - exit \n
|
|
'''
|
|
|
|
cv2.imshow('image',im)
|
|
while True:
|
|
k = cv2.waitKey(0)&0xFF
|
|
if k == ord('a'):
|
|
curve = hist_curve(im)
|
|
cv2.imshow('histogram',curve)
|
|
cv2.imshow('image',im)
|
|
print 'a'
|
|
elif k == ord('b'):
|
|
print 'b'
|
|
lines = hist_lines(im)
|
|
cv2.imshow('histogram',lines)
|
|
cv2.imshow('image',gray)
|
|
elif k == ord('c'):
|
|
print 'c'
|
|
equ = cv2.equalizeHist(gray)
|
|
lines = hist_lines(equ)
|
|
cv2.imshow('histogram',lines)
|
|
cv2.imshow('image',equ)
|
|
elif k == ord('d'):
|
|
print 'd'
|
|
curve = hist_curve(gray)
|
|
cv2.imshow('histogram',curve)
|
|
cv2.imshow('image',gray)
|
|
elif k == ord('e'):
|
|
print 'e'
|
|
norm = cv2.normalize(gray,alpha = 0,beta = 255,norm_type = cv2.NORM_MINMAX)
|
|
lines = hist_lines(norm)
|
|
cv2.imshow('histogram',lines)
|
|
cv2.imshow('image',norm)
|
|
elif k == 27:
|
|
print 'ESC'
|
|
cv2.destroyAllWindows()
|
|
break
|
|
cv2.destroyAllWindows()
|
|
|